Registration number: 19BCE1717
Faculty: Prof. Parvathi R
Slot: L55 + L56
Course code: CSE3020
Explore the lattice package in R using the HSB2 dataset and the builtin MTCars dataset. Run the code given in class
library(lattice)
df = read.csv("hsb2.csv")
head(df, 5)
## id female race ses schtyp prog read write math science socst
## 1 70 0 4 1 1 1 57 52 41 47 57
## 2 121 1 4 2 1 3 68 59 53 63 61
## 3 86 0 4 3 1 1 44 33 54 58 31
## 4 141 0 4 3 1 3 63 44 47 53 56
## 5 172 0 4 2 1 2 47 52 57 53 61
ses.f <-factor(df$ses,levels=c(1,2,3),
labels=c("ses_1","ses_2","ses_3"))
prog.f <-factor(df$prog,levels=c(1,2,3),
labels=c("prog_1","prog_2","prog_3"))
xyplot(df$read~df$write)
xyplot(df$read~df$write|ses.f*prog.f,
main="Scatterplots by Cylinders and Gears",
ylab="Miles per Gallon", xlab="Car Weight")
xyplot(read~write,
data = df,
type = c("p", "r"),
main = "Relation between Read and Write",
xlab = "Read Score",
ylab = "Write Score")
xyplot(df$read~df$write | ses.f,
data = df,
type = c("p", "r"),
groups = ses.f,
main = "Relation between Read and Write",
xlab = "Read Score",
ylab = "Write Score")
densityplot(~df$read,
main="Density Plot",
xlab="Read score")
densityplot(~df$read|ses.f, data = df,
main="Read Score by SES",
xlab="Read Score")
densityplot(~df$read|ses.f,
main="Density Plot by SES",
xlab="Read score",
layout=c(1,3))
densityplot(~df$read,
groups = ses.f,
plot.points = FALSE,
main = "Kernel density plot over SES",
xlab = "Read score")
bwplot(prog.f ~ df$read | ses.f,
xlab = "SES",
ylab = "Prog",
Main = "Prog given by SES")
bwplot(ses.f~df$read|prog.f,
ylab="SES", xlab="PROG",
main ="SES and Prog")
bwplot(prog.f ~ df$read |ses.f,
xlab = "READ score",
ylab = "PROG",
Main = "SES and read score",
layout = c(1, 3))
# 3 d plot
cloud(df$socst~df$science*df$math,main = "3D scatterplot")
cloud(df$science~df$math*df$socst|ses.f,
main="3D Scatterplot by SES")
dotplot(ses.f~df$read|prog.f,
main="Dotplot Plot by SES and prog",
xlab="Read score")
splom(df[c(1,3,4,5,6)],
main="hsb2 Data")
bwplot(prog.f ~ df$read | ses.f,
data = df,
xlab = "Read score",
ylab = "PROG",
Main = "PROG and SES",
panel = panel.violin)
data <- dimnames(volcano)
contour(x=volcano, xlab = "Row", ylab = "Column") # Contour plot for volcano dataset
filled.contour(volcano)
filled.contour(volcano,color.palette = terrain.colors)
library(lattice) # already imported from part 1
attach(mtcars)
mtcars
## mpg cyl disp hp drat wt qsec vs am gear carb
## Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4
## Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4
## Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1
## Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1
## Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2
## Valiant 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1
## Duster 360 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4
## Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2
## Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2
## Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4
## Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4
## Merc 450SE 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3
## Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3
## Merc 450SLC 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 3
## Cadillac Fleetwood 10.4 8 472.0 205 2.93 5.250 17.98 0 0 3 4
## Lincoln Continental 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3 4
## Chrysler Imperial 14.7 8 440.0 230 3.23 5.345 17.42 0 0 3 4
## Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1
## Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2
## Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1
## Toyota Corona 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3 1
## Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2
## AMC Javelin 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2
## Camaro Z28 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 4
## Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2
## Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1
## Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2
## Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2
## Ford Pantera L 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 4
## Ferrari Dino 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 6
## Maserati Bora 15.0 8 301.0 335 3.54 3.570 14.60 0 1 5 8
## Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 2
gear.f<-factor(gear,levels=c(3,4,5),
labels=c("3gears","4gears","5gears"))
cyl.f <-factor(cyl,levels=c(4,6,8),
labels=c("4cyl","6cyl","8cyl"))
xyplot(mpg~wt)
xyplot(mpg~wt|cyl.f*gear.f,
main="Scatterplots by Cylinders and Gears",
ylab="Miles per Gallon", xlab="Car Weight")
#XYplot 1
xyplot(mpg~wt,
data = mtcars,
type = c("p", "r"),
main = "Relation between wt and mpg",
xlab = "Weight in lbs",
ylab = "Miles/Gallon (US)")
#XYplot 2
xyplot(mpg~wt | cyl.f,
type = c("p", "r"),
groups = cyl.f,
main = "Relation between wt and mpg over cylinders",
xlab = "Weight in lbs",
ylab = "Miles/Gallon (US)")
xyplot(mpg~wt | cyl.f,
type = c("p", "r"),
groups = cyl.f,
main = "Relation between wt and mpg over cylinders",
xlab = "Weight in lbs",
ylab = "Miles/Gallon (US)")
densityplot(~mpg,
main="Density Plot",
xlab="Miles per Gallon")
densityplot(~mpg|cyl.f,
main="Density Plot by Number of Cylinders",
xlab="Miles per Gallon")
densityplot(~mpg|cyl.f,
main="Density Plot by Numer of Cylinders",
xlab="Miles per Gallon",
layout=c(1,3))
densityplot(~mpg,
groups = gear.f,
plot.points = FALSE,
main = "Kernel density plot over number of gears",
xlab = "Miles Per Gallon (US)")
bwplot(gear.f ~ mpg | cyl.f,
xlab = "Miles per Gallon (US)",
ylab = "No of Gears",
Main = "Mileage by no. of gears and cylinders")
bwplot(cyl.f~mpg|gear.f,
ylab="Cylinders", xlab="Miles per Gallon",
main ="Mileage by Cylinders and Gears")
bwplot(gear.f ~ mpg |cyl.f,
xlab = "Miles per Gallon (US)",
ylab = "No of Gears",
Main = "Mileage by no. of gears and cylinders",
layout = c(1, 3))
# 3 d plot
cloud(mpg~wt*qsec,main = "3D scatterplot")
cloud(mpg~wt*qsec|cyl.f,
main="3D Scatterplot by Cylinders")
dotplot(cyl.f~mpg|gear.f,
main="Dotplot Plot by Number of Gears and Cylinders",
xlab="Miles Per Gallon")
splom(mtcars[c(1,3,4,5,6)],
main="MTCARS Data")
bwplot(gear.f ~ mpg | cyl.f,
data = mtcars,
xlab = "Miles per Gallon (US)",
ylab = "No of Gears",
Main = "Mileage by no. of gears and cylinders",
panel = panel.violin)
data <- dimnames(volcano)
contour(x=volcano, xlab = "Row", ylab = "Column") # Contour plot for volcano dataset
filled.contour(volcano)
filled.contour(volcano,color.palette = terrain.colors)